Intelligent Utilization of a Unified Flow Pattern Prediction Model in Production System Optimization

Multiphase flow phenomena are widespread in nature and production process. The study of the flow mechanism and characteristics are a very important in the multiphase pipe flow. The establishment of multiphase flow experimental devices and systems is necessary in the study. In order to multi-phase pipe flow simulation, the small-scale physical experimental system based on the PLC control, and the experimental simulation system of based on Configuration software design are achieved. The physical experimental system can be achieved signals acquisition and control. Bubble flow, stratified flow, wavy flow, slug flow and other flow patterns can be formed in the experimental pipeline by changing the oil-gas-water flow rate. The virtual experimental system consists of the control interface and virtual physical interface. The simulation experiments of the multiphase flow generation can be achieved through the data exchange by two computers. This system meets the requirements for multiphase flow experiment.

An oil-water flow pattern classification and characterization for wellbores is proposed based on the integrated analysis of experimental data, including frictional pressure drop, holdup and spatial phase distribution, acquired in a transparent test section (2 in. ID, 51 ft long) using a refined mineral oil and water (=0.85, =20.0 and =33.5 dyne/cm at 90 F). The tests covered inclination angles of 90, 75, 60 and 45 from horizontal. The oil-water flow patterns have been classified into two major categories given by the status of the continuous phase, including water dominated flow patterns and oil dominated flow patterns. It was found that most water dominated flow patterns show significant slippage but relatively low frictional pressure gradients. In contrast, all the oil dominated flow patterns exhibit negligible slippage but significantly larger frictional pressure gradients. Six flow patterns have been characterized in upward vertical flow; three were water dominated and three were oil dominated. In upward inclined flow there were four water dominated flow patterns, two oil dominated flow patterns and a transitional flow pattern. Flow pattern maps for each of the tested inclination angles are presented. A mechanistic model to predict flow pattern transitions in vertical wells is proposed. The transitions to the very fine dispersed flow patterns were evaluated by combining the concepts of turbulent kinetic energy with the surface free energy of the droplets, while the transitions to the churn flow pattern and the phase inversion were predicted based on the concept of agglomeration. The model compares favorably with the measured data. Introduction Two-phase flow of oil and water is commonly encountered in wellbores; however, its hydrodynamic behavior under a wide range of flow conditions and inclination angles constitutes a relevant unresolved issue for the oil industry. Multiphase flows are characterized by the existence of diverse flow configurations or flow patterns, which can usually be identified by a typical geometrical arrangement of the phases in the pipe. Inherent to each flow pattern are characteristic spatial distributions of the interface, flow mechanisms and distinctive values for design parameters such as pressure gradient, holdup and heat transfer coefficient. There is clear evidence that accurate knowledge of oil-water flow patterns, their ranges of existence as a function of flow rates and pipe inclination angles, and values for their associated hydrodynamic parameters are crucial in a number of production engineering applications. These include production optimization, optimum string selection, production logging interpretation, -downhole metering and artificial lift design and modeling. Additionally, the understanding of oil-water flow in wellbores is fundamental in determining the volumes of free water in contact with the pipe that could cause scaling and corrosion of the pipe after prolonged exposure. This paper addresses the fundamental problem of identifying and characterizing oil-water flow patterns and predicting flow pattern transitions for conditions pertinent to oil-water producing wells. Literature Review Despite being a subject of permanent interest for the petroleum industry, the issue of oil-water flow patterns in wellbores has barely been addressed in the technical literature. A limited number of experimental studies have been found that provide a description of the flow patterns for low-medium viscosity oil and water. Govier et al. and Zavareh et al. conducted investigations in vertical flow, while Scott and Zavareh et al. covered inclinations near the horizontal and near the vertical, respectively. A larger number of related studies concentrated on measuring the holdup, mainly for oil dispersed systems, focusing on finding expressions for the slip velocity that could be used in the interpretation of production logs. P. 601^

The developments of oil and gas fields in deep waters (5000 ft and more) will become more common in the future. It is inevitable that production systems will operate under multiphase flow conditions (simultaneous flow of gas, oil and water possibly along with sand, hydrates, and waxes). Multiphase flow prediction tools are essential for every phase of hydrocarbon recovery from design to operation. Recovery from deep-waters poses special challenges and requires accurate multiphase flow predictive tools for several applications, including the design and diagnostics of the production systems, separation of phases in horizontal wells, and multiphase separation (topside, seabed or bottom-hole). It is crucial for any multiphase separation technique, either at topside, seabed or bottom-hole, to know inlet conditions such as flow rates, flow patterns, and volume fractions of gas, oil and water coming into the separation devices. Therefore, the development of a new generation of multiphase flow predictive tools is needed. The overall objective of the proposed study is to develop a unified model for gas-oil-water three-phase flow in wells, flow lines, and pipelines to predict flow characteristics such as flow patterns, phase distributions, and pressure gradient encountered during petroleum production at different flow conditions (pipe diameter and inclination, more » fluid properties and flow rates). In the current multiphase modeling approach, flow pattern and flow behavior (pressure gradient and phase fractions) prediction modeling are separated. Thus, different models based on different physics are employed, causing inaccuracies and discontinuities. Moreover, oil and water are treated as a pseudo single phase, ignoring the distinct characteristics of both oil and water, and often resulting in inaccurate design that leads to operational problems. In this study, a new model is being developed through a theoretical and experimental study employing a revolutionary approach. The basic continuity and momentum equations is established for each phase, and used for both flow pattern and flow behavior predictions. The required closure relationships are being developed, and will be verified with experimental results. Gas-oil-water experimental studies are currently underway for the horizontal pipes. Industry-driven consortia provide a cost-efficient vehicle for developing, transferring, and deploying new technologies into the private sector. The Tulsa University Fluid Flow Projects (TUFFP) is one of the earliest cooperative industry-university research consortia. TUFFP's mission is to conduct basic and applied multiphase flow research addressing the current and future needs of hydrocarbon production and transportation. TUFFP participants and The University of Tulsa are supporting this study through 55% cost sharing. « less

Previous multiphase pipe flow tests have mainly been conducted in horizontal and vertical pipes, with few tests conducted on multiphase pipe flow under different inclined angles. In this study, in light of mid–high yield and highly deviated wells in the Middle East and on the basis of existent multiphase flow pressure research on well bores, multiphase pipe flow tests were conducted under different inclined angles, liquid rates, and gas rates. A pressure prediction model based on Mukherjee model, but with new coefficients and higher accuracy for well bores in the study block, was obtained. It was verified that the newly built pressure drawdown prediction model tallies better with experimental data, with an error of only 11.3%. The effect of inclination, output, and gas rate on the flow pattern, liquid holdup, and friction in the course of multiphase flow were analyzed comprehensively, and six kinds of classical flow regime maps were verified with this model. The results showed that for annular and slug flow, the Mukherjee flow pattern map had a higher accuracy of 100% and 80–100%, respectively. For transition flow, Duns and Ros flow pattern map had a higher accuracy of 46–66%.

Distinguished Author Series articles are general, descriptiverepresentations that summarize the state of the art in an area of technology bydescribing recent developments for readers who are not specialists in thetopics discussed. Written by individuals recognized as experts in the area, these articles provide key references to more definitive work and presentspecific details only to illustrate the technology. Purpose: to informthe general readership of recent advances in various areas of petroleumengineering. Summary. Multiphase flow can occur throughout the production system. Thefluids involved in multiphase flow in the petroleum industry are multicomponentmixtures with complex phase behavior. Petroleum engineers are faced with theneed to predict the relationships between flow rates, pressure drop, and piping(geometry or reservoir fluids produced during, the life of a field. This paperreviews the historical (Development of design tools used to address theseunique multiphase-flow features. State-of-the-art technology is alsopresented. Introduction Multiphase flow can occur throughout the entire production system involvedin flowing fluids from oil and gas reservoirs to processing facilities at thesurface. The production system in this context includes the reservoir: the wellcompletion: the tubulars that connect the reservoir to the surface: all surfacefacilities on land, seabed. or offshore platform and any pipelines that carryproduced fluids to other processing facilities. The multiphase flow encounteredin producing oil and gas can be any combination of a saturations phase, ahydrocarbon liquid phase, and a water phase. A vast amount of technical information on multiphase flow in pipes isavailable in the literature. Many of these sources are related to otherindustries and involve different types of- fluids. The reference list for thispaper clearly demonstrates the diversity of interest in multiphase flow inpipes. In particular, significant contributions have been made in the nuclearindustry. where a major concern is a possible loss-of--coolant accident in anuclear reactor. These studies involve the transient simulation of two-phase, single-component (water) fluid flow in piping systems. Multiphase flow in the petroleum industry has many unique features thatcreate complications not encountered by other industries. The fluids involvedare multicomponent mixtures whose phase behavior is extremely complex. Therange of pressures and temperatures encountered in production systems isextremely broad. Pressures can range from 15.000 psia [100 MPa] to nearatmospheric conditions. Temperatures can range from 400deg.F [200deg.C) to below the freezing, temperature of water. Pipe lengths can vary from a few feet to several hundredmiles for surface pipe or pipelines and from a few hundred feet to more than20,000 ft (6100) mi for wells. Piping, systems often involve significantvariations in (geometry, such as inclination angle. Diameter, pipe roughness, and even shape, such as when fluids flow in the annular space between casingand tubing in a wellbore. Although most vertical piping systems involve upflow, it is not uncommon to have multiphase downward flow in injection wells ordowncomers connecting, offshore platforms to subsea pipelines. Simulationmultiphase flow in wells also requires the ability to predict fluidtemperatures in a system that undergoes complex heat transfer phenomena betweenthe reservoir and the surface. The entire wellbore is surrounded by a huge rockvolume, much of which may even be frozen, as in the case of permafrost inarctic locations. Engineers in the petroleum industry are faced with the requirement topredict the relationships between flow rates, pressure drop, and pipinggeometry (length, diameter, angle, etc.) for the fluids produced from areservoir over the entire life of the field. The objective of this paper is toreview the historical development of design tools used to address the uniquemultiphase-flow features of the petroleum industry, including an evaluation ofthe state of the art. JPT P. 15^

Solid particle erosion is a major problem in many industrial applications where solids are entrained in gas and/or liquid flows. For example, erosion of production equipment, well tubing and fittings is a major operating problem that costs the petroleum industry millions of dollars each year. Entrained sand particles in the oil/gas production fluid impinge on the inner surfaces of the pipes, fittings, and valves that result in solid particle erosion. In certain production situations with corrosive fluids, erosion is compounded with corrosion causing severe erosion-corrosion. Even in situations when sand control means are utilized such as gravel packing and sand screens, small sand particles can plug sand screens promoting higher flow velocities through other portions of the screens causing failure and allowing sand production. Erosion can cause severe damage to the piping and equipment wall, resulting in loss of equipment and production downtime. Solid particle erosion is a mechanical process by which material is removed gradually from a solid surface due to repeated impingement of small solid particles on the metal surface. The erosion phenomenon is highly complicated due to the number of parameters affecting the erosion severity, such as production flow rate, sand rate, fluid properties, flow regime, sand properties, sand shape and size, wall material of equipment, and geometry of the equipment. For ductile materials, erosion is caused by localized deformation and cutting action from repeated particle impacts. It is well known that solid particle erosion rates are a strong function of the impacting velocity of particles and also the mass of impacting particles. Predicting solid particle erosion in multiphase flow is a complex task due to existence of different flow patterns. The existence of different flow patterns and sand and liquid holdup in vertical and horizontal pipes means that a unique erosion model has to be developed for each flow regime if the model is to account for the number and velocity of impacting particles. The particle impact velocity is affected by the pipe geometry, carrying fluid properties and velocity, flow pattern, particle size and distribution in the flow. Among different multiphase flow patterns in horizontal and vertical flows, severe erosion damage can occur in annular and slug flows with high gas velocities and low liquid velocities. Although there is a lack of accurate mechanistic models to predict solid particle erosion, there is a need to develop engineering prediction models for multiphase flows. Earlier erosion calculation procedures in multiphase flow were primarily based on empirical data and the accuracy of those “empirical” models was limited to the flow conditions of the experiments. A framework for developing a model has been established for predicting erosion rates of elbows in multiphase flow. The model considers the effects of particle velocities in gas and liquid phases upstream of the elbow. Local fluid velocities in multiphase flow are used to determine representative particle impact velocities. Also based on data representing sand holdup for several flow regimes, the masses of impacting particles are estimated. Erosion experiments are also conducted on elbows in two-inch and three-inch large scale multiphase flow loops with gas, liquid and sand flowing in vertical and horizontal test sections. Based on the experimental data for different flow regimes including slug, wet gas and annular flow a method for improving a previous model is discussed and is being implemented to predict erosion rates in multiphase flow.

The wellbore of a sucker–rod pumping well experiences a multi–phase flow consisting of oil, gas, and water. The flow pattern and pump discharge pressure are greatly impacted by oil well production, which in turn significantly affects the simulation results of longitudinal vibration in the sucker–rod string. When calculating the discharge pressure in a hydrostatic column containing both oil and water (HC), the pressure is not affected by the oil well’s production. This thereby avoids interference between vibrations in the sucker–rod string’s longitudinal direction and the flow from the wellbore. Considering the coupling characteristics between the longitudinal vibration of the sucker–rod string and the wellbore flow, a mathematical model of the sucker–rod pumping system (CMSRS) and a mathematical model of the downhole energy efficiency parameters were established. In detail, the CMSRS comprises two parts: the discharge pressure mathematical models of multi–phase flow dynamics (MD) and the wave equation of the longitudinal vibration of the sucker–rod string. A numerical simulation model of the sucker–rod pumping system was constructed based on a mathematical model. We compared the experimental results, the simulation results of the CMSRS and the simulation results of the sucker–rod string based on the oil–water two–phase hydrostatic column (SMSRS) and found good agreement, indicating the feasibility of the CMSRS. The simulation details show the following: (1) The HC model’s discharge pressure exceeds that of the MD model by more than 33.52%. The polished rod load for the CMSRS is 18.01% lower than that of the SMSRS, and the pump input power for the CMSRS is 36.23% lower than that of the SMSRS. (2) The effective power simulation model based on the energy balance relationship is essentially the same as the effective power calculated by the model based on multi–phase flow effective power. This validates the accuracy of the multi–phase flow effective power model. (3) The limitations of the industry standard effective power model are that (i) the effective head is the net lift height of the fluid in the wellbore reduced to the oil and water phases rather than the effective lift height based on the energy balance relationship and (ii) the power of the gas phase delivered by the pumping pump is disregarded, and only the effective power of the pump delivering the oil–water mixture is considered. (4) The influence of the wellbore parameters on the wellbore efficiency and sub–efficiency is systematically analyzed. The analysis results have an important significance in the guidance of energy saving in pumping wells.

New empirical PVT correlations for estimating bubblepoint pressure, solution gas-oil ratio, bubblepoint oil formation volume factor and undersaturated isothermal oil compressibility have been developed as a function of commonly available field data. Results show that these PVT properties can be predicted with average absolute errors ranging from 0.64% for bubblepoint oil formation volume factor to 6.66% for undersaturated isothermal oil compressibility.

Introduction. Prediction of multiphase flow patterns in pipelines of gas and oil industry is a complicated hydrodynamic process. Hydraulics of gas-liquid flows and erosion processes in pipelines with many bends in which gas, water, oil and air move are insufficiently studied. There are known studies of movement in single-phase flow conditions with one elbow, which is insufficient for design of modern pipeline systems. Therefore, there is a need for in-depth analysis of interaction of media in multiphase flow and transported sand particles. In this paper the effects of elbows on multiphase flow hydraulics and erosion of pipe sections are investigated using computational fluid dynamics (CFD) modelling tools for 100 seconds’ of process. Materials and methods. A liquid volume model (VOF) was used to simulate three-phase flow: air-water with solids in a pipe with two elbows. Turbulence effects have been accounted for with the RNG k–ε model. The model verification methods from previous studies have been used. For the numerical solution, the Ansys Fluent version 20.1 software package has been used. The results of CFD modelling of the volumetric gas content have shown a good agreement with the available experimental data. Results. The results showed that the change in the flow regime remains unchanged before the first elbow and after the se-cond elbow in the cork flow. However, for the initial churn flow regime, the flow regime varies at different segments of the flow area before and after each elbow. Conclusions. The preliminary churn flow in the upper vertical section was transformed to wavy stratified flow in the horizontal section between the two elbows and wavy annular flow in the vertical pipe after the second elbow. The flow pattern in slug flow maintained same after the first elbow, but the Taylor bubbles are lengthier in the horizontal section between the first and second elbows.

CFD Simulations of Abnormal Flow in Horizontal Pipes for Offshore Hydrocarbon Transport

Pressure traverse in multiphase flow differs from single phase flow due to the differential flow rates of the different phases. Correlations developed to predict multiphase flow pressure traverse are mostly for vertical wells but Beggs and Brill model is one of the few models that is used for inclined pipes. The work seeks to show the improvement in the modification of the model. This project is based on studies carried out on multiphase fluid flow in pipes of any inclination using the Beggs and Brill flow model as the focus. Two cases were considered, the liquid holdup correction and Gas Liquid Ratio (GLR) variations in which the Beggs and Brill and Beggs and Brill Traverse models were compared. Due to the empirical nature of the Beggs and Brill model, pressure gradient predictions are far from accurate when compared with measured data in the field. This

This study describes the development and validation of an improved simplified model for transient two-phase flow for any pipe inclination. The simplified model proposed has been validated with field-scale test well and laboratorial data, and also compared to the state-of-the-art commercial simulator for transient two-phase flow in pipes. The results of the simplified model showed an agreement within the range of ±30% for the holdup predictions for 65% of the scenarios, and an agreement within the range of ±30% for the pressure predictions for 82% of the scenarios considered in this work. In the oil and gas industry, transient two-phase flow is present in many production and drilling operations, such as in well unloading, well control, and managed pressure drilling. There are many commercial transient multiphase flow simulators available, which use complex numerical procedures to describe multiphase flow in pipes and estimate variables of interest, such as pressure, temperature, phase fractions, and flow regimes discretized in space and time. Many of the transient flow scenarios encountered in the industry are considered slow transients and a rigorous transient simulator may not be necessary in these cases. With a few simplifications of the fundamentals equations, less complex models can be deployed in such cases without significantly compromising the accuracy of the results. With this consideration, and taking the fact that acquiring a license of a commercial software can be prohibitive for small operators and consulting companies, an easy-to-use and open source simulator was implemented based on the simplified transient model discussed in this work.

With the ongoing increase in global energy demand, the significance of innovations in oil exploration and development technologies is rising, especially in relation to the development of unconventional reservoirs. The application of horizontal wells is becoming increasingly important in this particular situation. However, accurately monitoring and analyzing fluids in horizontal wells remains challenging due to the complex and fluctuating flow patterns of oil-water two-phase flow within the wellbore. Several elements, including well slope angle, flow rate, and water content, are involved. This study aimed to explore and develop an effective method for forecasting flow patterns, improving the precision of the dynamic monitoring of oil-water two-phase flow in horizontal wells. By analyzing the flow patterns in different experimental conditions, a predictive model using the SOA-BP neural network was developed, providing a scientific basis for dynamic monitoring in actual production scenarios. Initially, the simulated experiment for oil-water two-phase flow was carried out at room temperature and pressure utilizing a multiphase flow simulator. An optically transparent wellbore, with a diameter comparable to that of a real downhole well, was utilized, and No. 10 industrial white oil and tap water were employed as the experimental fluids. The experiment considered multiple contributing factors, including different well deviation, total flow, and water cut. The flow characteristics of oil and water were observed via visual monitoring and high-definition video, followed by detailed analysis. After collecting the experimental data, flow regimes for various scenarios were classified based on the established theory of oil-water two-phase flow in horizontal wells; then, detailed flow distribution diagrams were drawn. These data and diagrams presented offer a visual representation of the behavioral patterns exhibited by oil-water two-phase flow under varying situations and form the basis for subsequent model training and testing. Subsequently, based on the experimental data, this study combined the Seagull Optimization Algorithm (SOA) with a BP neural network to effectively learn and predict the experimental data. The SOA optimized the weights and biases of the BP neural network, improving the model’s convergence speed and prediction accuracy. Through rigorous training and testing, an oil-water two-phase flow pattern forecasting model was established, effectively predicting flow patterns under different well deviation, total flow, and water cut conditions. Finally, to validate the efficiency of the established model, a total of 15 data points were chosen from a sample well for validation. By comparing the flow patterns predicted by the model with actual logging data, the results indicate that the model’s accuracy in identifying flow pattern was 86.67%. This demonstrates that the flow pattern prediction model based on the SOA-BP neural network achieved a high level of accuracy under different complicated working conditions. This model effectively fulfills the requirements for dynamic monitoring in actual production. This indicates that the SOA-BP neural network-based flow pattern forecasting method is highly valuable due to its practical application value and provides an efficient technical approach for the development of unconventional reservoirs and the dynamic monitoring of horizontal wells in the future.

Reform of the drift-flux model of multiphase flow in pipes, wellbores, and reactor vessels

Some industrials processes are associated with flow of non-Newtonian fluids in annular spaces. Examples are found in oil industry and food industrial processing. In some cases, gravitational forces cause internal pipe deflection and, consequently, the eccentricity changes along of axis of the annular space. So, flow patterns are modified respect to those found in constant eccentricity annular spaces. Current industrial practice consists on extrapolate predictions based on flow patterns from the constant eccentricity critical scenario, corresponding to the critical region where both boundaries are closer, to the variable eccentricity actual scenario. In practice, using this approach, flow pattern predictions could significantly deviate from the actual profile, and variables such as shear stress at walls or pressure gradient could not be estimated with adequate accuracy. This work consists of a Computational Fluid Dynamics study, aimed to state the implications of evaluating flow patterns, assuming constant eccentricity, in opposition to a more realistic scenario, considering deflection path along the annular space, using a commercial code. A particular application is made to mud removal during well cementing operations in oil industry. For the casing in the hole, the deflection equation is solved and eccentricity along of the system axis is found. Flow of a non-Newtonian fluid described by Power Law model is considered. Oil industry typical conditions are considered for fluid density, rheological parameters, flow rates, casing and hole sizes, and annulus eccentricity. The flow regime was considered laminar. Numerical model capability to reproduce accurately flow patterns in these conditions was assured by comparison with others analytical-numerical solutions for concentric systems. Results show that local Reynolds number Re, shear stress τw and pressure gradient predictions G, under local eccentricity variations, differ from those under constant eccentricity. Differences in Re and τw show a maximum for eccentricity ranging from 60% to 80%, for all flow conditions whereas for G, this difference increases as casing deflection does it. When variable eccentricity models are compared to constant eccentricity one, the latter approach underestimates Re and τw along the narrowest section of the annuli, whereas overestimates the same features along the widest clearance. Additionally, considerably higher variations between these two models are taking place along the narrowest section compared to the variations arising on the widest annular section. When applied to well cementing processes, these results show that considering the most realistic scenario may impact significantly the flow pattern prediction on the annulus during primary cementing operations. Therefore, the quality of the cement job may be greatly compromised.